In this interview, we dive into the transformative impact of technology on the future of work with Dr. Daniel Susskind, a Research Professor in Economics at King’s College London, and a Senior Research Associate at the Institute for Ethics in AI at Oxford University. His insights offer valuable perspectives on AI, automation, and their implications for the future of work.
Tatiana Chesniak: As an economist and writer, you've extensively researched the impact of technology on labor markets. Could you tell me what initially sparked your interest in the topic and why you chose to explore the future of work?
Daniel Susskind: Every day we hear stories of systems and machines that are taking on tasks and activities that until recently we thought only human beings alone could ever do. Making medical diagnoses and driving cars, drafting legal contracts and designing buildings, composing music and writing news reports. What does all of this mean for the vast majority of us for whom our job is our main, if not our only, source of income? I think this is one of the greatest questions of our time, and that's why I've spent the last ten years thinking about it.
Tatiana: That perspective is fascinating. Could you outline how artificial intelligence and automation are set to reshape the workforce in the coming years?
Daniel: The emergence of AI and technology presents one big challenge: while these innovations create work for people to do, not everyone is necessarily able to do that work. You know, one reason might be that people do not have the right skills or capabilities to do the work. This poses a significant challenge over the next couple of decades—how to retrain individuals in the skills demanded by these new roles. It’s not a challenge of mass unemployment, but a challenge of mass redeployment that we are facing.
Tatiana: Is there something people can do to future-proof their careers in this shifting job landscape?
Daniel: Broadly, I can outline two strategies. First, mastering skills that compete with the tasks AI is not very good at doing, such as creative, communication, and problem-solving tasks. The alternative is cultivating skills that involve designing, operating, and building these technologies.
So, simply put, either you want to try and be the sort of person who can compete with these technologies or you want to be the sort of person who can build these technologies. What you should not be doing is training to do the sorts of routine activities that these technologies are already very good at doing.
Tatiana: This should provide a clear direction for people who are worried about their jobs. Moving on, with AI's rise, what are the types of jobs you anticipate will emerge or expand due to these advancements?
Daniel: I think it's critical to shift our focus from "jobs" to specific tasks and activities that become vital in the AI era. It is natural that due to changes in the landscape, some tasks will vanish while others gain significance. For instance, the tasks that define a nurse's role today significantly differ from those a few decades ago, even though the job title remains unchanged. So the question we should be asking instead is what sorts of tasks and activities are going to be valuable and important?
And to answer that, I think it’s the tasks that I outlined before. You're going to want to either learn to do tasks that allow you to compete with these systems and machines, or to do tasks that allow you to build them.
Tatiana: Turning your attention to organizations, what guidance would you offer decision-makers, particularly CTOs and CIOs, for determining the right approach for adopting AI into their business?
Daniel: I think the most important thing to have in mind if you're the leader of an organization is “What problem am I trying to solve for my clients and my customers? And can I use these technologies to solve that problem in a different way?” That's one of the themes in my work, to encourage leaders to focus relentlessly on outcome-based thinking rather than process-based thinking. The true challenge lies in leveraging technology to enhance the result, regardless of the traditional processes they are used to.
AI's Creative Side
Tatiana: Your perspective emphasizes the importance of focusing on results. Do you have some non-ordinary examples of AI applications?
Daniel: Sure! What's so interesting about the latest wave of technology, but also exciting and troubling in some ways, is that it's not just doing the routine repetitive work anymore. It's starting to take on the sorts of tasks and activities that until recently we thought only the most expert human beings could do. It’s not simply using systems and machines to perform, say, complex calculations, but we can now use them to write code. The sort of thing that might have required a really creative software engineer in the past, we can now do through technology. And this, I think, is what we're seeing happen across the working world, that these technologies are moving from the world of routine and repetitive work into the world of non-routine complex work. And as I said, that's what I think is so exciting about it. But also what's so for some people, unsettling.
Tatiana: Sounds like we should prepare ourselves to see lots of expert-level jobs to be overtaken by AI.
Daniel: That's right. Think, for instance, of Chat GPT. One of the things that people were saying until very recently is that technology will never be able to perform tasks that require creativity from human beings. And yet that is what GPT or indeed the whole family of technologies is particularly good at doing.
Tatiana: Indeed, we can see the transition to using AI in completing creative tasks, among others, already happening. Although there is still some uncertainty as to how AI adoption will develop and unfold, I think we should think about harmonizing AI with humans already. How do you think can we design AI technologies that augment humans rather than replace them?
Daniel: I think the question of how can we change the direction of technological progress in a way that we think is more beneficial to human beings is probably the most important question facing leaders and people who are designing these technologies. And I think there are lots of different ways we can do it.
Let me give you one example from the tax system. There’s a lot of evidence from the US, for instance, that the US tax system provides a very strong incentive for leaders to use a machine to do a task rather than employ a human being. After all, if you use a machine, you don't have to bother with payroll tax and you don't have all the complexities of employment law and so on. And right now there is interesting work going on in the US that is aimed at changing the incentives in the tax system to encourage business leaders to do the opposite, to use workers rather than use machines. And that's the sort of question I think policymakers around the world need to be grappling with, not only regarding tax systems.
Tatiana: Seems like a lot of policy adjustments will need to happen in order to prevent this from spreading further. Speaking of policies, what trends do you foresee in AI regulations, particularly within Europe?
Daniel: One of the challenges that we face at the moment is that the sort of regulatory framework that we have in lots of areas of our working lives was designed for a very different economic environment. The challenge is that technologies like AI are allowing people that aren't traditional doctors or traditional lawyers or traditional accountants to perform the type of work that might have required a professional in the past. So that regulatory environment that we built to shape the behavior of a particular type of worker or institution simply no longer applies. So in answer to your question, what's going to happen to the regulation in Europe? I think it's going to need to be overhauled.
Unlocking the Potential of AI for Your Business
Tatiana: What would you tell companies that have not yet started their AI journey? What do they need to consider?
Daniel: The core question is whether AI is perceived as a threat or an opportunity. If you try and resist these technological trends, if you're on the technological backfoot, then I think what is taking place is probably quite threatening.
But in my opinion, these technologies are very exciting. They're a great opportunity. They offer ways to solve the problems that you currently solve more efficiently and effectively than ever before. I would just point out that these technologies are an opportunity if they're embraced and probably a threat if they're ignored.
When thinking about technology, what you really want to do is start with a blank sheet of paper, forget the particular institution that you're part of, forget the particular ways in which things might have been done in the past, and instead ask, given the outcomes that you are trying to achieve as an organization, how can you use technology to achieve those outcomes in fundamentally different ways?
Tatiana: So basically, the beginning of the AI journey is the time to step aside from everything that has been followed over the years, and instead take a new look at your business.
Daniel: Exactly. Because again, the temptation is to ask, how can I use technology to do what I've always done, but more efficiently, more effectively? And that’s where you miss the real opportunity.
Tatiana: I think that perfectly sums up the importance of outcome-based thinking when looking at ways of embracing AI. Looking ahead, what do you consider the most promising applications of AI in the near future?
Daniel: The most interesting, I think, is going to be the development of what's known as “affective computing”. These are systems in machines that are designed to both detect and respond to human emotions. There is a lot of very interesting work going on at the moment about the use of technology in tasks that might have required interpersonal interaction or the personal touch of human beings before. And this, I think, is one of the more striking and more troubling developments that's taking place, the use of technology in this world that we really did think would necessarily involve human beings.
Tatiana: Thank you for sharing these insights. I am now even more intrigued by your upcoming speech at Digitalize and Automate 2023. Could you offer a sneak peek into what attendees can expect?
Daniel: Sure. What I'll be wanting to do is to describe what's really taking place in the world of technology at the moment. There's so much hype and excitement about what's happening in AI. I want to look beneath some of that hype and try and identify the most important things that are happening in the world of technology. I will also identify what this means for the future of work.
And I also want to focus on what people should actually do about all of these ideas to bring it back down to earth. I’ll nail down the sorts of things that as a leader, as an employee, you ought to be thinking about and preparing to flourish in the future to come.
Tatiana: I’m looking forward to hearing more. Thank you for the valuable insights you've shared with us today.
Daniel: I appreciate the opportunity. Thank you.
To explore AI's impact on productivity and IT processes further and find out concrete ways to embrace the change, we invite you to join our free annual event, Digitalize and Automate 2023.
Don’t miss the opportunity to watch Daniel’s keynote LIVE on September 19!
Tatiana is a Content Marketing Specialist at Efecte. Driven by her passion for marketing, she provides different types of content that reflect Efecte as a European market leader, an innovator in their space, and a bright place to work. Her professional goals include engaging the readers and shaping a strong image of Efecte in people’s minds.
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